Iowa State University/CTRE NCRST-I Projects

Iowa State University/CTRE NCRST-I Projects

About CTRE

• Center for Transportation Research and Education• Iowa State University/CCE• Interdisciplinary MS Transportation• Midwest Transportation Consortium (USDOT)• 80+ year partnership with Iowa DOT• 75 projects/$4M budget

Team Philosophy• Focus on DOT needs• Develop synergy with other projects

– LRS, pavement management, GIS, crash systems, Asset management/GASB 34

• Build on TRB/Pecora typology/thesis– Applications– Technologies– Issues (cost, accuracy, resolution, temporal …)

• Graduate Education/Extension (Outreach)

Functions:• Engineering

– Traffic Engineering– Transportation

Safety• Maintenance• Motor Vehicle

– Driver Services– Motor Carrier

Services• Planning and

Programming– Program

Management– Project Planning– Systems Planning

• Project Development– Bridges and

Structures– Construction– Contracts– Design– Materials– Right of Way

• Street Addresses/911• Hydrology• Land cover• Land use• Wells• underground storage tanks• wetlands• driver data• crash (crash, driver/

vehicle, injury)• entrances• reference points• traffic and vehicle

classification• Boundaries (jurisdiction)• markings and condition• bridges/structures• soils• environment• Cadastral• Roadside features• signs/ control devices• speed limit/ no passing• intermodal facility• navigational waterways• ports• airports and runways• drainage• weight limits• garages• truck routes• grade• curve • surface/structure

• RR crossing and traffic• clearances/size limits• deer kill

Data: • resources (fuels, materials)• Adopt-a-Highway

• Cartography• Photogrammetry• Videolog• CAD - as builts

crashes = f(land use)

• no. of lanes/ functional class

• road/name/route• shoulder

Functions:• Engineering









WWW roadway weather conditions• Street Addresses/911• Hydrology• Land cover• Land use• Wells• underground storage tanks• wetlands• driver data• crash (crash, driver/


classification• Boundaries

(jurisdiction)• markings and condition• bridges/structures• soils• environment• Cadastral• Roadside features• signs/ control devices• speed limit/ no passing• intermodal facility• navigational waterways• ports• airports and runways• drainage• weight limits• garages• truck routes• grade• curve





• road/name/route• shoulder• surface/structure

Asset ManagementFunctions:• Engineering

– Traffic Engineering

– Transportation Safety

• Maintenance• Motor Vehicle
















GIS - Crash Location and AnalysisFunctions:• Engineering


















Team Philosophy• Focus on DOT needs• Develop synergy with other projects

– LRS, pavement management, GIS, crash systems, Asset management/GASB 34

• Build on TRB/Pecora typology/thesis– Applications– Technologies– Issues (cost, accuracy, resolution, temporal …)

• Graduate Education/Extension (Outreach)

From: Cowen, D.J. and J.R. Jensen, People and Pixels, 1998.

Potential for RS Applications in Transportation

1.1 Satellite/Space Based

1.2 Aerial/Airplane Based

1.3 In-situ (Video/Magnetic)

2.1.1 Traffic Counting, Classification & Analysis2.1.2 Observation of Intermodal Behavior2.1.3 Visualization and Exploratory Data Analysis2.2.1 Assessment of Transportation Emissions2.2.2 Relationships between theTransportation Infrastructure and the Environment2.2.3 Corridor Analysis and Planning2.2.4 Assess and Model the Impacts ofClimate Variability and Change on Transportation Networks

2.3.1 Traveler Information Systems2.3.2 Regional Disaster Assessment and Response

2.4.1 Physical Inventory2.4.2 Condition Assessment

2.3 Hazards, Safety, and Disaster Response

2.4 Infrastructure Management

Type of SensingApplications

2.1 Transportation FlowAssessment

2.2 EnvironmentalAssessment

Information Available

Further Researchor Beyond Scope

Information Available for VideoInconsistent for Magnetic

Further Research for VideoInconsistent for Magnetic

Inconsistent

Application n

Low Altitude Aerial Photography

Calib

rate/

Valid

ate

Plann

ing

Mod

els

Issu

es

Time: Considerably faster than performing an O/D study or manual counts. No driver disruption.Cost: For peak hour model, cost of one flight during peak periodAvailability: Off the shelf technology, pictures can be taken every 15 minutesEase of use: photos will need to be manually interpretedAccuracy: Images can be blown up in order to see vehicles, resolution & scale not really a concern for counting vehiclesApplicability: Could have other uses although not corrected for distortions or scaleLabor: Less labor intensive than previous ways

Type o

f Sen

sing

Applic

ation

ISU/CTRE Stakeholders

• Iowa DOT/MTC match @1/3• Local IDOT Steering Committee

– Photogrammetry– GIS Coordinator– Research/Videolog

• Ian MacGillivray– IDOT Research/Engineering Director– Steering Committee– Speaker at DC conf

ISU/CTRE Team• R. Souleyrette, PI

– 12 years (UNLV Nuke Waste/ISU GIS-T)– TRB GIS-T, Iowa DOT GIS

• S. Hallmark, PM– Assistant Professor of Civil Engineering– PhD GaTech– LRS, safety, vehicular dynamics, air quality

• 3 MS students (2 CE, 1 Trans)

ISU/CTRE Projects

1. Access Management

2. Pavement and Marking Condition

3. Infrastructure Point Features/LRS Control

Project #1: Access Management

• Balance access and mobility

• Improve traffic flow and safety

• Local issue … businesses

• Rural issue … safety

Access Management

1 Mile = 1.60943 Kilometers

Safety Impact of Access Control Crash rate per hundred-million

Vehicle Kilometers

Urban Rural

Access Control Total Fatal Total Fatal

Full 116 1 94 2

Partial 308 3 131 4

None 327 2 206 6

Source: Garber & Hoel 1999

source: http://www.fhwa.dot.gov/////realestate/am_mich.pdf

The Problem

• US Crash cost $150B+ per year (NHTSA)

• System-wide crash data now available

• No comprehensive inventory available

• On-road data collection is resource intensive

Access Related Data Elements

• Access roads– Presence– Configuration

• Driveways– Number– Dimensions– Frequency– Continuity– Vertical grade

• Medians– Type– Length

• Turn lanes– Length– Material

• Intersections– Proximity– Frequency

The Opportunity

• Correlate access w/crash history

• Determine relationships

• Identify hot spots

• Identify system deficiencies

Research Approach• Identify features of interest• Collect ground truth• Extract features from imagery (quantitative)• Estimate quality of access (qualitative)• Correlate measures with crash rates• Determine quality of data required to support

analysis• Work with partners on machine-assisted extraction

Sample Imagery

Project #2: Pavement and Marking Condition

Pavement Condition - The Problem

• Pavement/shoulder type– Inventory element– Safety concern

• Pavement condition assessment– Input to pavement management system– Requires field data collection

• Pavement condition analysis – Visual inspection/expert judgment is subjective– PMIS data collection is expensive

Research Approach: Pavement Condition Evaluation

• Identify measures obtainable from imagery– Cracks (by type)

– Pavement type

– Rutting (LIDAR?)

• Validate (IPMP Roadware Van)• Benefit-cost analysis

Pavement Markings - The Problem• Pavement markings

– Wear out variably– Replaced on regular basis, or on “complaint”

• Marking program not directly dependent on condition– Remaining life is unknown– Maintenance expense

Research Approach - Pavement Marking Condition

• Evaluate spatial, spectral, temporal and radiometric requirements– Current marking visibility– Retro-reflectivity (surrogate measures?)– Remaining life

• Buffer vectors to reduce computational requirements of hyperspectral (subpixel analysis)

• Test available data and specify requirements• Evaluate benefit of a systematic method

Project #3: Infrastructure Point Features/LRS Control

The Problem/Opportunity

• DOTs have huge spatial datasets and many LRMs• NCHRP 20-27 LRS model (Vonderohe/Adams)

– LRS relates methods

– Iowa is early implementer

• Inventory of large systems is expensive– 110,000 miles of road in Iowa

Iowa DOT LRS

• LRS datum = anchor points and anchor sections

• Control located using highly accurate methods (RTK GPS, etc.)

• Pilot did not test satellite imagery

from anchor pointto anchor point

L1 @195 m

L1 @353 m

L1 @604 m

L1 @781 m

L1 @908 m

anchor section = 1164 m

Point Infrastructure Elements• Pixel

– Roadway intersection

– Bridge abutments – Drainage structures– Railroad crossings– Ramp gore point

• Sub-pixel?– Signs– Mileposts– Utility access covers– Telephone poles

Approach• Evaluate ability to extract features based on resolution

w/partner institutions– pixel/sub-pixel– image interpretation/machine assisted

• Collect validation data (GPS)• Statistical comparison RS vs.GPS• Define resolution (SSTR) requirements• Benefit/cost analysis

60'

36'

Road Segment

Potential Future Projects• Linear, areal and temporal features• Intersection sight distance• Elderly driver issues• Vegetation growth• Snow drifting/hydrology• Parking Inventory

Questions/Suggestions?

Documents

Iowa State University/CTRE NCRST-I Projects